1 Tekrarlanabilir Analiz ve Rapor


1.2 Replication Crisis Excel Version


2 RStudio ile proje oluştur


3 R Notebook

3.1 R Notebook dökümanı oluşturma


3.2 R Notebook’tan html, pdf ve word oluşturma


3.3 RNotebook vs RMarkdown

https://youtu.be/zNzZ1PfUDNk


4 R Markdown

4.1 Hem kendi kodları hem de html kodları yazılabilir

https://rmarkdown.rstudio.com

What is R Markdown? from RStudio, Inc. on Vimeo.


4.2 R Markdown: The Definitive Guide

https://bookdown.org/yihui/rmarkdown/


4.4 Remedy Package


4.4.1 Remedy


4.6 Render Markdown via code

inside R

markdown::markdownToHTML('markdown_example.md', 
'markdown_example.html')

command line

R -e "markdown::markdownToHTML('markdown_example.md',
'markdown_example.html')"

4.7 pandoc Rstudio integration

command line

export PATH=$PATH:/Applications/RStudio.app/Contents/MacOS/pandoc
R -e "rmarkdown::render('markdown_example.md')"

5 RMarkdown chunk içinde R kodlarını çalıştırma

{r, results='asis'}
 iris %>%
  tibble::as_tibble() %>%
  details::details(summary = 'tibble')

6 Metin arasında R kodlarını çalıştırma


7 Chunk Options

7.1 Global Options

{r global_options 1, include=FALSE}
knitr::opts_chunk$set(fig.width = 12,
                      fig.height = 8,
                      fig.path = 'Figs/',
                      echo = FALSE,
                      warning = FALSE,
                      message = FALSE,
                      error = FALSE,
                      eval = TRUE,
                      tidy = TRUE,
                      comment = NA)

7.2 Other Code Languages


8 R Markdown kod örneği

{r}
data("cancer")
cancer
foreign::write.foreign(df = cancer,
                        datafile = "data/cancer.sav",
                        codefile = "data/cancer.spo",
                        package = "SPSS"
                        )

9 R Markdown Paket Çağırma 📦

{r}
suppressPackageStartupMessages(library("tidyverse"))
suppressPackageStartupMessages(library("survival"))

9.1 Sık kullandığım paketler 📦

{tidyverse} {tidylog}

{lubridate} {janitor}

{readxl} {foreign}

{summarytools} {ggstatsplot} {tangram} {finalfit} {psycho} {jmv}

{survival} {survminer}

{report} {kableExtra}


10 R Markdown Veri Yükleme SPSS


11 R Markdown Veri Yükleme Excel


12 Veri Görüntüleme

{r}
View(mydata)
glimpse(mydata)

13 Veri Düzenleme

{r}
mydata <- janitor::clean_names(mydata)
{r}
mydata$sontarih <- janitor::excel_numeric_to_date(
  as.numeric(mydata$olum_tarihi)
  )

14 Recode

{r}
mydata$Outcome <- "Dead"
mydata$Outcome[mydata$olum_tarihi == "yok"] <- "Alive"
{r}
## Recoding mydata$cinsiyet into mydata$Cinsiyet
mydata$Cinsiyet <- recode(mydata$cinsiyet,
               "K" = "Kadin",
               "E" = "Erkek")
mydata$Cinsiyet <- factor(mydata$Cinsiyet)

15 Recode regular expression

{r recode TNM stage}
#pT2N0Mx -> 2
mydata$Tstage <- stringr::str_match(
  mydata$patolojik_evre, 
  paste('(.+)', "N", sep=''))[,2]
)

16 Recode regular expression case_when

{r recode TNM2}
mydata <- mydata %>% 
    mutate(
        T_stage = case_when(
            grepl(pattern = "T1", x = .$Tstage) == TRUE ~ "T1",
            grepl(pattern = "T2", x = .$Tstage) == TRUE ~ "T2",
            grepl(pattern = "T3", x = .$Tstage) == TRUE ~ "T3",
            grepl(pattern = "T4", x = .$Tstage) == TRUE ~ "T4",
            TRUE ~ "Tx"
        )
    )

17 Recode regular expression case_when

{r}
mydata <- mydata %>% 
    mutate(
TumorPDL1gr1 = case_when(
        t_pdl1 < 1 ~ "kucuk1",
        t_pdl1 >= 1 ~ "buyukesit1"
    )
    )

18 R Markdown Tanımlayıcı İstatistikler

{r}
library(summarytools)
view(dfSummary(colon_s))

A beginner kit for #rstats The Landscape of R Packages for Automated Exploratory Data Analysis https://journal.r-project.org/archive/2019/RJ-2019-033/

@article{RJ-2019-033, author = {Mateusz Staniak and Przemysław Biecek}, title = {{The Landscape of R Packages for Automated Exploratory Data Analysis}}, year = {2019}, journal = {{The R Journal}}, doi = {10.32614/RJ-2019-033}, url = {https://journal.r-project.org/archive/2019/RJ-2019-033/index.html} }


18.1 Table One

{r, results='asis'}
# cat(names(mydata), sep = " + \n")
library(arsenal)
tab1 <- tableby(~ Cinsiyet + 
Yas + 
TumorYerlesimi
                ,
                data = mydata)
summary(tab1)

18.3 Kategorik Veriler

{r}
mydata %>% 
  janitor::tabyl(Categorical) %>%
  adorn_pct_formatting(rounding = 'half up',
                       digits = 1) %>%
  knitr::kable()
{r crosstable}
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE) -> table
knitr::kable(table, row.names = FALSE, align = c('l', 'l', 'r', 'r', 'r'))

18.4 Kategorik Veriler için Grafikler

{r ggstatplot, layout='l-page'}
mydata %>% 
    ggstatsplot::ggbarstats(data = .,
                            main = Categorical_variable,
                            condition =  dependent_variable
                            )

18.5 Continious Variables

{r}
mydata %>% 
jmv::descriptives(
    data = .,
    vars = c(yas),
    hist = TRUE,
    dens = TRUE,
    box = TRUE,
    violin = TRUE,
    dot = TRUE,
    mode = TRUE,
    sd = TRUE,
    variance = TRUE,
    skew = TRUE,
    kurt = TRUE,
    quart = TRUE)

19 R Markdown örneği Çapraz Tablolar

{r crosstable}
library(finalfit)
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       column = TRUE,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE,
                       na_include=FALSE
                       # catTest = catTestfisher
                       ) -> table
knitr::kable(table,
             row.names = FALSE,
             align = c('l', 'l', 'r', 'r', 'r'))

20 R Markdown örneği Sağkalım

20.1 Sağkalım için veriyi düzenleme

{r define survival time}
mydata$int <- lubridate::interval(
  lubridate::ymd(mydata$CerrahiTarih),
  lubridate::ymd(mydata$SonTarih)
  )
mydata$OverallTime <- lubridate::time_length(mydata$int, "month")
mydata$OverallTime <- round(mydata$OverallTime, digits = 1)
{r}
## Recoding mydata$Outcome into mydata$Outcome2
mydata$Outcome2 <- recode(mydata$Outcome,
               "Alive" = "0",
               "Dead" = "1")
mydata$Outcome2 <- as.numeric(mydata$Outcome2)

20.2 Kaplan-Meier

{r Kaplan-Meier}
mydata %>%
  finalfit::surv_plot(dependent,
                      explanatory,
                      xlab='Time (months)',
                      pval=TRUE,
                      legend = 'none',
                      break.time.by = 12,
                      xlim = c(0,60),
                      legend.labs = c('a','b')
)

20.3 Sağkalım Tabloları

{r}
km_fit <- survfit(dependent ~ explanatory,
                  data = mydata)
km_fit
{r, eval=FALSE, include=FALSE}
library(survival)
km <- with(mydata, Surv(OverallTime, Outcome2))
# head(km,80)
# plot(km)
{r 1-3-5-yr}
summary(km_fit, times = c(12,36,60))

20.4 Pairwise comparison

{r}
survminer::pairwise_survdiff(formula = Surv(time, Outcome) ~ Group, 
                             data = mydata,
                             p.adjust.method = "BH")

20.5 Multivariate Analysis Survival

{r Multivariate Analysis, eval=FALSE, include=FALSE}
library(finalfit)
library(survival)
explanatoryMultivariate <- explanatoryKM
dependentMultivariate <- dependentKM
mydata %>%
  finalfit(dependentMultivariate, explanatoryMultivariate) -> tMultivariate
knitr::kable(tMultivariate, row.names=FALSE, align=c("l", "l", "r", "r", "r", "r"))

21 jamovi

21.1 jamovi ve R entegrasyonu

Rj Editor – Analyse your data with R in jamovi


21.2 {jmv} paket kodları

jamovi syntax mode


22 Güncellemeler olunca kodlar çalışacak mı?


22.1 Paket Kütüphaneleri

  • packrat / renv

https://environments.rstudio.com


22.2 Docker

  • docker

22.2.1 The Rocker Project

Docker Containers for the R Environment

docker run --rm -ti rocker/r-base

Or get started with an RStudio® instance:

docker run -e PASSWORD=yourpassword --rm -p 8787:8787 rocker/rstudio

and point your browser to localhost:8787 Log in with user/password rstudio/yourpassword


Managing containers


22.3 Yeni R sürümleri

  • RSwitch

https://rud.is/rswitch/

  • Using RSwitch

https://rud.is/rswitch/guide/

: scale 30%


23 Yedeklemeyi nasıl yapacağız

23.1 Projeyi düzgün organize edin

  • pdf
  • R
  • images
  • bib
{r load library}
source(file = here::here("R", "loadLibrary.R"))

23.2 Save Final Data

{r}
saved data after analysis to `mydata.xlsx`.

save.image(file = here::here("data", "mydata_work_space.RData"))

readr::write_rds(x = mydata, path = here::here("data", "mydata_afteranalysis.rds"))

saveRDS(object = mydata, file = here::here("data", "mydata.rds"))

writexl::write_xlsx(mydata, here::here("data", "mydata.xlsx"))

paste0(rownames(file.info(here::here("data", "mydata.xlsx"))), " : ", file.info(here::here("data", "mydata.xlsx"))$ctime)

23.3 GitHub

{r github push}
CommitMessage <- paste("updated on ", Sys.time(), sep = "")
wd <- getwd()
gitCommand <- paste("cd ", 
                    wd,
                    " \n git add . \n git commit --message '",
                    CommitMessage,
                    "' \n git push origin master \n",
                    sep = ""
                    )
system(command = gitCommand,
       intern = TRUE
)

23.4 GitHub Yedekleme

CommitMessage <- paste("updated on ", Sys.time(), sep = "")
wd <- getwd()
gitCommand <- paste("cd ", 
                    wd,
                    " \n git add . \n git commit --message '",
                    CommitMessage,
                    "' \n git push origin master \n",
                    sep = ""
                    )
system(command = gitCommand,
       intern = TRUE
)

24 Her dökümanın sonuna kullandığınız kütüphaneler için atıf yazdırabilirsiniz

{r}
citation()

24.1 Libraries Used

citation()

24.2 Bu oturuma spesifik kullanılan paketler

report::cite_packages(session = sessionInfo())

24.3 Tek tek paket atıfları

{r library citations}
citation("tidyverse")
citation("readxl")
citation("janitor")
citation("report")
citation("finalfit")
citation("ggstatplot")

24.4 Jamovi ve R için atıf örneği


25 Her dökümanın sonuna oturum detaylarınızı yazdırabilirsiniz

{r session info, echo=TRUE}
sessionInfo()

25.1 Session Info

sessionInfo()

26 Sonraki Konular

  • RStudio ile GitHub kullanımı

29 Geri Bildirim




  1. Bu bir derlemedir, mümkün mertebe alıntılara linklerle referans vermeye çalıştım.↩︎

---
title: R, RStudio ve RMarkdown ile Tekrarlanabilir Rapor^[Bu bir derlemedir, mümkün mertebe alıntılara linklerle referans vermeye çalıştım.]
author: "[Serdar Balcı, MD, Pathologist](https://sbalci.github.io/)"
institute: "[serdarbalci.com](https://www.serdarbalci.com)"
date: "`r format(Sys.Date())`"
output:
  revealjs::revealjs_presentation:
    incremental: true
    theme: sky
    highlight: pygments
    center: false
    smart: true
    transition: fade
    self_contained: true
    ig_width: 7
    fig_height: 6
    fig_caption: true
    reveal_options:
      slideNumber: true
      previewLinks: true
  rmdshower::shower_presentation:
  xaringan::moon_reader:
    lib_dir: libs
    nature:
      beforeInit: ["macros.js", "https://platform.twitter.com/widgets.js"]
      highlightStyle: github
      highlightLines: true
      countIncrementalSlides: false
    self_contained: true
  html_notebook:
    fig_caption: yes
    highlight: kate
    number_sections: yes
    theme: flatly
    toc: yes
    toc_depth: 5
    toc_float: yes
  prettydoc::html_pretty:
    theme: leonids
    highlight: github
  pdf_document:
    toc: yes
    toc_depth: '5'
  html_document:
    fig_caption: yes
    keep_md: yes
    toc: yes
    toc_depth: 5
    toc_float: yes
editor_options: 
  chunk_output_type: inline
---


<!-- Open all links in new tab-->  
<base target="_blank"/>  


<!-- Go to www.addthis.com/dashboard to customize your tools --> <script type="text/javascript" src="//s7.addthis.com/js/300/addthis_widget.js#pubid=ra-5bc36900a405090b">  
</script>



```{r global_options, include=FALSE}
knitr::opts_chunk$set(fig.width = 12, fig.height = 8, fig.path = 'Figs/', echo = FALSE, warning = FALSE, message = FALSE, error = FALSE, eval = TRUE, tidy = TRUE, comment = NA, cache = TRUE)
```



```{r eval=FALSE, message=FALSE, warning=FALSE, include=FALSE}
# xaringan::inf_mr()
# servr::daemon_stop(1)
```



# Tekrarlanabilir Analiz ve Rapor


[![](https://the-turing-way.netlify.com/figures/reproducibility/ReproducibleMatrix.jpg)](https://the-turing-way.netlify.com/reproducibility/03/definitions.html)




---


## Replication Crisis

![](figures/replicationCrisis.png)

https://en.wikipedia.org/wiki/Replication_crisis


---

## Replication Crisis Excel Version

[![](figures/geneNamesExcel.png)](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1044-7)


---

# RStudio ile proje oluştur



![](images/RStudio-NewProject.gif)



---

# R Notebook  

## R Notebook dökümanı oluşturma 


![](images/RNotebook1.gif)

---

## R Notebook'tan html, pdf ve word oluşturma  


![](images/RNotebook2.gif)


---

## RNotebook vs RMarkdown  

<iframe width="560" height="315" src="https://www.youtube.com/embed/zNzZ1PfUDNk" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>  

https://youtu.be/zNzZ1PfUDNk


---

# R Markdown

## Hem kendi kodları hem de html kodları yazılabilir

https://rmarkdown.rstudio.com

<iframe src="https://player.vimeo.com/video/178485416?color=428bca&title=0&byline=0&portrait=0" width="640" height="400" frameborder="0" allow="autoplay; fullscreen" allowfullscreen></iframe>
<p><a href="https://vimeo.com/178485416">What is R Markdown?</a> from <a href="https://vimeo.com/rstudioinc">RStudio, Inc.</a> on <a href="https://vimeo.com">Vimeo</a>.</p>

---

## R Markdown: The Definitive Guide

https://bookdown.org/yihui/rmarkdown/


---

## R Markdown syntax

https://gist.github.com/MinhasKamal/7fdebb7c424d23149140


<script src="https://gist.github.com/MinhasKamal/7fdebb7c424d23149140.js"></script>



---

## Remedy Package  

[<img src="https://raw.githubusercontent.com/ThinkR-open/remedy/master/reference/figures/thinkr-hex-remedy.png" width=250px>](https://github.com/ThinkR-open/remedy)


---

### Remedy  

[<img src="https://raw.githubusercontent.com/ThinkR-open/remedy/master/reference/figures/remedy_example.gif" width=500px>](https://github.com/ThinkR-open/remedy)


---

## R Markdown paket ve şablonları  

https://bookdown.org/yihui/rmarkdown/document-templates.html


![](images/RMarkdownTemplates.gif)


---

## Render Markdown via code

*inside R*

```
markdown::markdownToHTML('markdown_example.md', 
'markdown_example.html')
```

*command line*

```
R -e "markdown::markdownToHTML('markdown_example.md',
'markdown_example.html')"
```

---


## pandoc Rstudio integration

*command line*

```
export PATH=$PATH:/Applications/RStudio.app/Contents/MacOS/pandoc
```


```
R -e "rmarkdown::render('markdown_example.md')"
```


---

# RMarkdown `chunk` içinde `R` kodlarını çalıştırma


```
{r, results='asis'}
 iris %>%
  tibble::as_tibble() %>%
  details::details(summary = 'tibble')
```

---

# Metin arasında `R` kodlarını çalıştırma


![](images/inlineRCode.png)


---

# Chunk Options

## Global Options

```
{r global_options 1, include=FALSE}
knitr::opts_chunk$set(fig.width = 12,
                      fig.height = 8,
                      fig.path = 'Figs/',
                      echo = FALSE,
                      warning = FALSE,
                      message = FALSE,
                      error = FALSE,
                      eval = TRUE,
                      tidy = TRUE,
                      comment = NA)
```

---

## Other Code Languages


[![](https://d33wubrfki0l68.cloudfront.net/162347ef5afe219da22fb7d7d9a5989f2c3e5a85/59316/lesson-images/languages-1-demos.png)](https://rmarkdown.rstudio.com/lesson-5.html)


---


# R Markdown kod örneği  


```
{r}
data("cancer")
cancer
foreign::write.foreign(df = cancer,
                        datafile = "data/cancer.sav",
                        codefile = "data/cancer.spo",
                        package = "SPSS"
                        )
```


---

# R Markdown Paket Çağırma 📦    


```
{r}
suppressPackageStartupMessages(library("tidyverse"))
suppressPackageStartupMessages(library("survival"))
```

---

## Sık kullandığım paketler 📦  

{tidyverse}
{tidylog}

{lubridate}
{janitor}

{readxl}
{foreign}

{summarytools}
{ggstatsplot}
{tangram}
{finalfit}
{psycho}
{jmv}

{survival}
{survminer}

{report}
{kableExtra}

---

# R Markdown Veri Yükleme SPSS  

![](images/importSPSS.gif)


---

# R Markdown Veri Yükleme Excel  



![](images/importExcel.gif)


---

# Veri Görüntüleme


```
{r}
View(mydata)
glimpse(mydata)
```




---

# Veri Düzenleme

```
{r}
mydata <- janitor::clean_names(mydata)
```

```
{r}
mydata$sontarih <- janitor::excel_numeric_to_date(
  as.numeric(mydata$olum_tarihi)
  )
```


---

# Recode


```
{r}
mydata$Outcome <- "Dead"
mydata$Outcome[mydata$olum_tarihi == "yok"] <- "Alive"
```


```
{r}
## Recoding mydata$cinsiyet into mydata$Cinsiyet
mydata$Cinsiyet <- recode(mydata$cinsiyet,
               "K" = "Kadin",
               "E" = "Erkek")
mydata$Cinsiyet <- factor(mydata$Cinsiyet)
```


---

# Recode regular expression


```
{r recode TNM stage}
#pT2N0Mx -> 2
mydata$Tstage <- stringr::str_match(
  mydata$patolojik_evre, 
  paste('(.+)', "N", sep=''))[,2]
)
```


---

# Recode regular expression case_when

```
{r recode TNM2}
mydata <- mydata %>% 
    mutate(
        T_stage = case_when(
            grepl(pattern = "T1", x = .$Tstage) == TRUE ~ "T1",
            grepl(pattern = "T2", x = .$Tstage) == TRUE ~ "T2",
            grepl(pattern = "T3", x = .$Tstage) == TRUE ~ "T3",
            grepl(pattern = "T4", x = .$Tstage) == TRUE ~ "T4",
            TRUE ~ "Tx"
        )
    )
```

---

# Recode regular expression case_when

```
{r}
mydata <- mydata %>% 
    mutate(
TumorPDL1gr1 = case_when(
        t_pdl1 < 1 ~ "kucuk1",
        t_pdl1 >= 1 ~ "buyukesit1"
    )
    )
```

---

# R Markdown Tanımlayıcı İstatistikler  


```
{r}
library(summarytools)
view(dfSummary(colon_s))
```


---


A beginner kit for #rstats
The Landscape of R Packages for Automated Exploratory Data Analysis
https://journal.r-project.org/archive/2019/RJ-2019-033/



@article{RJ-2019-033,
  author = {Mateusz Staniak and Przemysław Biecek},
  title = {{The Landscape of R Packages for Automated Exploratory Data
          Analysis}},
  year = {2019},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2019-033},
  url = {https://journal.r-project.org/archive/2019/RJ-2019-033/index.html}
}



---


## Table One  


```
{r, results='asis'}
# cat(names(mydata), sep = " + \n")
library(arsenal)
tab1 <- tableby(~ Cinsiyet + 
Yas + 
TumorYerlesimi
                ,
                data = mydata)
summary(tab1)
```

---

## The Grammar of Tables


[tangram: The Grammar of Tables](https://cran.r-project.org/web/packages/tangram/)

[A grammar of tables](https://github.com/leeper/tttable)

[Grammar of Tables?](https://gist.github.com/leeper/f9cfbe6bd185763762e126a4d8d7c286)

[Easily generate information-rich, publication-quality tables from R](https://gt.rstudio.com)


---

## Kategorik Veriler

```
{r}
mydata %>% 
  janitor::tabyl(Categorical) %>%
  adorn_pct_formatting(rounding = 'half up',
                       digits = 1) %>%
  knitr::kable()
```

```
{r crosstable}
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE) -> table
knitr::kable(table, row.names = FALSE, align = c('l', 'l', 'r', 'r', 'r'))
```

---

## Kategorik Veriler için Grafikler  

```
{r ggstatplot, layout='l-page'}
mydata %>% 
    ggstatsplot::ggbarstats(data = .,
                            main = Categorical_variable,
                            condition =  dependent_variable
                            )
```

---


## Continious Variables

```
{r}
mydata %>% 
jmv::descriptives(
    data = .,
    vars = c(yas),
    hist = TRUE,
    dens = TRUE,
    box = TRUE,
    violin = TRUE,
    dot = TRUE,
    mode = TRUE,
    sd = TRUE,
    variance = TRUE,
    skew = TRUE,
    kurt = TRUE,
    quart = TRUE)
```

---

# R Markdown örneği Çapraz Tablolar  

```
{r crosstable}
library(finalfit)
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       column = TRUE,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE,
                       na_include=FALSE
                       # catTest = catTestfisher
                       ) -> table
knitr::kable(table,
             row.names = FALSE,
             align = c('l', 'l', 'r', 'r', 'r'))
```

---

# R Markdown örneği Sağkalım  

- Drawing Survival Curves Using ggplot2  
https://rpkgs.datanovia.com/survminer/reference/ggsurvplot.html

## Sağkalım için veriyi düzenleme

```
{r define survival time}
mydata$int <- lubridate::interval(
  lubridate::ymd(mydata$CerrahiTarih),
  lubridate::ymd(mydata$SonTarih)
  )
mydata$OverallTime <- lubridate::time_length(mydata$int, "month")
mydata$OverallTime <- round(mydata$OverallTime, digits = 1)
```

```
{r}
## Recoding mydata$Outcome into mydata$Outcome2
mydata$Outcome2 <- recode(mydata$Outcome,
               "Alive" = "0",
               "Dead" = "1")
mydata$Outcome2 <- as.numeric(mydata$Outcome2)
```

---

## Kaplan-Meier

```
{r Kaplan-Meier}
mydata %>%
  finalfit::surv_plot(dependent,
                      explanatory,
                      xlab='Time (months)',
                      pval=TRUE,
                      legend = 'none',
                      break.time.by = 12,
                      xlim = c(0,60),
                      legend.labs = c('a','b')
)
```

---

## Sağkalım Tabloları

```
{r}
km_fit <- survfit(dependent ~ explanatory,
                  data = mydata)
km_fit
```

```
{r, eval=FALSE, include=FALSE}
library(survival)
km <- with(mydata, Surv(OverallTime, Outcome2))
# head(km,80)
# plot(km)
```

```
{r 1-3-5-yr}
summary(km_fit, times = c(12,36,60))
```

---

## Pairwise comparison

```
{r}
survminer::pairwise_survdiff(formula = Surv(time, Outcome) ~ Group, 
                             data = mydata,
                             p.adjust.method = "BH")
```

---

## Multivariate Analysis Survival

```
{r Multivariate Analysis, eval=FALSE, include=FALSE}
library(finalfit)
library(survival)
explanatoryMultivariate <- explanatoryKM
dependentMultivariate <- dependentKM
mydata %>%
  finalfit(dependentMultivariate, explanatoryMultivariate) -> tMultivariate
knitr::kable(tMultivariate, row.names=FALSE, align=c("l", "l", "r", "r", "r", "r"))
```

---

# jamovi

## jamovi ve R entegrasyonu

[Rj Editor – Analyse your data with R in jamovi](https://blog.jamovi.org/2018/07/30/rj.html)

![](images/jamoviRjEditor.gif)

---

## {jmv} paket kodları

[jamovi syntax mode](https://www.jamovi.org/user-manual.html#syntax-mode)


![](images/jamoviSyntaxMode.gif)



---

# Güncellemeler olunca kodlar çalışacak mı?


---

## Paket Kütüphaneleri

- packrat / renv

https://environments.rstudio.com

---

## Docker

- docker

---

### The Rocker Project

Docker Containers for the R Environment

```
docker run --rm -ti rocker/r-base
```

Or get started with an RStudio® instance:

```
docker run -e PASSWORD=yourpassword --rm -p 8787:8787 rocker/rstudio
```

and point your browser to [localhost:8787](localhost:8787)
Log in with user/password rstudio/yourpassword 

---

[![](images/TheRockerProject.png)](https://www.rocker-project.org)

[Managing containers](https://www.rocker-project.org/use/managing_containers/)


---

## Yeni R sürümleri 

- RSwitch

https://rud.is/rswitch/

- Using RSwitch

https://rud.is/rswitch/guide/


![: scale 30%](https://rud.is/rswitch/guide/menu-info.png)


---

# Yedeklemeyi nasıl yapacağız

## Projeyi düzgün organize edin

- pdf
- R
- images
- bib

```
{r load library}
source(file = here::here("R", "loadLibrary.R"))
```

---

## Save Final Data

```
{r}
saved data after analysis to `mydata.xlsx`.

save.image(file = here::here("data", "mydata_work_space.RData"))

readr::write_rds(x = mydata, path = here::here("data", "mydata_afteranalysis.rds"))

saveRDS(object = mydata, file = here::here("data", "mydata.rds"))

writexl::write_xlsx(mydata, here::here("data", "mydata.xlsx"))

paste0(rownames(file.info(here::here("data", "mydata.xlsx"))), " : ", file.info(here::here("data", "mydata.xlsx"))$ctime)

```

---

## GitHub  

```
{r github push}
CommitMessage <- paste("updated on ", Sys.time(), sep = "")
wd <- getwd()
gitCommand <- paste("cd ", 
                    wd,
                    " \n git add . \n git commit --message '",
                    CommitMessage,
                    "' \n git push origin master \n",
                    sep = ""
                    )
system(command = gitCommand,
       intern = TRUE
)
```

---

## GitHub Yedekleme

```{r github push, echo=TRUE}
CommitMessage <- paste("updated on ", Sys.time(), sep = "")
wd <- getwd()
gitCommand <- paste("cd ", 
                    wd,
                    " \n git add . \n git commit --message '",
                    CommitMessage,
                    "' \n git push origin master \n",
                    sep = ""
                    )
system(command = gitCommand,
       intern = TRUE
)
```

---

# Her dökümanın sonuna kullandığınız kütüphaneler için atıf yazdırabilirsiniz

```
{r}
citation()
```

---

## Libraries Used  

```{r library citation, echo=TRUE}
citation()
```

---

## Bu oturuma spesifik kullanılan paketler  

```{r library citation as report, echo=TRUE, results='asis'}
report::cite_packages(session = sessionInfo())
```


---

## Tek tek paket atıfları


```
{r library citations}
citation("tidyverse")
citation("readxl")
citation("janitor")
citation("report")
citation("finalfit")
citation("ggstatplot")
```


---

## Jamovi ve R için atıf örneği

- The jamovi project (2019). jamovi. (Version 0.9) [Computer Software]. Retrieved from https://www.jamovi.org.

- R Core Team (2018). R: A Language and envionment for statistical computing. [Computer software]. Retrieved from https://cran.r-project.org/.

- Fox, J., & Weisberg, S. (2018). car: Companion to Applied Regression. [R package]. Retrieved from https://cran.r-project.org/package=car.



---

# Her dökümanın sonuna oturum detaylarınızı yazdırabilirsiniz  

```
{r session info, echo=TRUE}
sessionInfo()
```

---

## Session Info

```{r session info, echo=TRUE}
sessionInfo()
```

---

# Sonraki Konular

- RStudio ile GitHub kullanımı
- ...

---

# Önerilen Kaynaklar

- [Reproducible Templates for Analysis and Dissemination](https://www.coursera.org/learn/reproducible-templates-analysis/home/info)

- [Happy Git and GitHub for the useR](https://happygitwithr.com/)





---

# Sunum Linkleri

https://sbalci.github.io/MyRCodesForDataAnalysis/R-Markdown.nb.html
https://sbalci.github.io/MyRCodesForDataAnalysis/R-Markdown.html

https://forms.gle/UqGJBiAjB8uLPRon8

---

# Geri Bildirim

- Geri bildirim için tıklayınız: _[Geri bildirim formu](https://goo.gl/forms/YjGZ5DHgtPlR1RnB3)_


---

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<div id="disqus_thread"></div>
<script>

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---

# İletişim  

Completed on `r Sys.Date()`.  

Serdar Balci, MD, Pathologist  
drserdarbalci@gmail.com  

https://rpubs.com/sbalci/CV   
https://sbalci.github.io/  
https://github.com/sbalci  
https://twitter.com/serdarbalci


---

   



---


# Other Links


https://andrewbtran.github.io/NICAR/2018/workflow/docs/02-rmarkdown.html

- Troubleshooting in R Markdown

https://smithcollege-sds.github.io/sds-public/rmarkdown_problems.html


http://kbroman.org/knitr_knutshell/pages/Rmarkdown.html

https://kbroman.org/knitr_knutshell/pages/overview.html

https://kbroman.org/knitr_knutshell/pages/Rmarkdown.html

https://kbroman.org/knitr_knutshell/pages/markdown.html


https://onp4.com/



```
csv {headers: true, title: "**Drawing Tables In Markdown**"}
Name, Surname, Known As, Age
Marcelo, David, coldzera, 22
Oleksandr, Kostyliev, s1mple, 19
Nikola, Kovač, NiKo, 20
Richard, Papillon, shox, 25
Nicolai, Reedtz, dev1ce, 21
```

```
{pgn}
[Event "Bled-Zagreb-Belgrade Candidates"]
[Site "Bled, Zagreb & Belgrade YUG"]
[Date "1959.10.11"]
[Round "20"]
[Result "1-0"]
[White "Mikhail Tal"]
[Black "Robert James Fischer"]

1. d4 Nf6 2. c4 g6 3. Nc3 Bg7 4. e4 d6 5.
Be2 O-O 6. Nf3 e5 7. d5 Nbd7 8. Bg5 h6 9.
Bh4 a6 10. O-O Qe8 11. Nd2 Nh7 12. b4 Bf6
13. Bxf6 Nhxf6 14. Nb3 Qe7 15. Qd2 Kh7 16.
Qe3 Ng8 17. c5 f5 18. exf5 gxf5 19. f4 exf4
20. Qxf4 dxc5 21. Bd3 cxb4 22. Rae1 Qf6 23.
Re6 Qxc3 24. Bxf5+ Rxf5 25. Qxf5+ Kh8 26.
Rf3 Qb2 27. Re8 Nf6 28. Qxf6+ Qxf6 29. Rxf6
Kg7 30. Rff8 Ne7 31. Na5 h5 32. h4 Rb8 33.
Nc4 b5 34. Ne5 1-0
```


- Keeping Credentials Secret with Keyrings in R

https://ras44.github.io/blog/2019/01/19/keeping-credentials-secret-with-keyrings-in-r.html

- How to build a website with Blogdown in R

http://www.storybench.org/how-to-build-a-website-with-blogdown-in-r/
